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They do not report doing a test of statistical significance on whether it is really smaller or not. Among insiders, women get more requests accepted than men. Among insiders, people are biased towards women, that is, revealing genders gives women an advantage over men above and beyond the case where genders are hidden. Among outsiders, women still get more requests accepted than men. Among outsiders, revealing genders appears to show a bias against women.It’s not clear if this is statistically significant. When all genders are revealed among outsiders, men appear to have their requests accepted at a rate of 64%, and women of 63%.Because Git Hub is big and their study is automated, they manage to get a really nice sample size – about 2.5 million pull requests by men and 150,000 by women. ) requests accepted than men for all of the top ten programming languages.

They admit that obvious-men also do worse than gender-anonymized men, but they ignore this effect because it’s smaller.

In other words, if you know somebody’s a woman, you’re more likely to approve her request than you would be on the merits alone.

We can’t quantify exactly how much this is, because the paper doesn’t provide numbers, just graphs.

The study itself say that women do worse than men when gender is revealed, so since the researchers presumably have access to their real numbers data, that might mean the confidence intervals don’t overlap.

From eyeballing the graph, it looks like the difference is 1% – ie, men get their requests approved 64% of the time, and women 63% of the time.

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